Numerical determination for solving the symmetric eigenvector problem using genetic algorithm

Navarro-González, Francisco J.; Compañ, Patricia; Satorre, R.; Villacampa, Yolanda

doi:10.1016/j.apm.2015.12.015

Cited by 9 publications

(5 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several questions must be considered in this step. Firstly, the presented algorithm continues the line of work developed by the authors in previous papers, see [3,4,78], solving the common bottleneck caused by the dependence of the time of computation on the complexity of the model at orders O((c + 1) 3d ) and O((c + 1) d ). Now, the dependence on the dimension has an expression of d•2 d .…”

Section: Discussionmentioning

confidence: 85%

Numerical Non-Linear Modelling Algorithm Using Radial Kernels on Local Mesh Support

et al. 2020

Self Cite

View full text Add to dashboard Cite

Estimation problems are frequent in several fields such as engineering, economics, and physics, etc. Linear and non-linear regression are powerful techniques based on optimizing an error defined over a dataset. Although they have a strong theoretical background, the need of supposing an analytical expression sometimes makes them impractical. Consequently, a group of other approaches and methodologies are available, from neural networks to random forest, etc. This work presents a new methodology to increase the number of available numerical techniques and corresponds to a natural evolution of the previous algorithms for regression based on finite elements developed by the authors improving the computational behavior and allowing the study of problems with a greater number of points. It possesses an interesting characteristic: Its direct and clear geometrical meaning. The modelling problem is presented from the point of view of the statistical analysis of the data noise considered as a random field. The goodness of fit of the generated models has been tested and compared with some other methodologies validating the results with some experimental campaigns obtained from bibliography in the engineering field, showing good approximation. In addition, a small variation on the data estimation algorithm allows studying overfitting in a model, that it is a problematic fact when numerical methods are used to model experimental values.

show abstract

Section: Discussionmentioning

confidence: 85%

Numerical Non-Linear Modelling Algorithm Using Radial Kernels on Local Mesh Support

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, it changes with direction for anisotropic materials, as shown for composite material layup of a 61.5 m and 100 m long blade in [24,33]. In this study, blade properties, required to achieve a desired mass, stiffness, and modal response, are optimized using a genetic algorithm [3,32], discussed later in Section 5. The blade thickness (t) and its gradient (S) from the optimized design solution (DS) are used to calculate the mechanical properties of each blade airfoil, as shown in this section.…”

Section: Estimation Of Airfoil Propertiesmentioning

confidence: 99%

“…Similarly, (q2-q3) and (q3-q2) is the shear flow acting on a length-to-thickness ratio a23 and a23 along the wall FD. Thus, solving Equation (30) to (32) for q1, q2, and q3 and Equation (29) for T, the torsional stiffness (J) for an airfoil stiffened with two webs can be obtained through Equation (22)…”

Section: Stiffened Bladementioning

confidence: 99%

“…These variables are obtained using a meta-heuristic, problem-independent optimization method, known as the genetic algorithm (GA) [29][30][31]. The method has been proven efficient and robust to solve complex eigenvalue problems [32], also for the purpose of optimizing the performance of OWT towers [3], the shape of composite blades [24,25], wind farm layouts [26][27][28], etc. In this study, the objective is to minimize the difference between the target [19] and estimated blade mass, stiffness, and modal response using the optimal design solution (DS), i.e., a set of the aforementioned variables.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Finite element modeling optimization of wind turbine blades from an earthquake engineering perspective

Ali

Risi

Sextos

2020

Engineering Structures

View full text Add to dashboard Cite

“…This study presents an FE integrated genetic algorithm (GA) based blade optimisation. GA is a problemindependent optimisation method, proven to robustly solve complex eigenvalue problems [16], optimise wind turbine tower performance [3], composite blade shapes [24,25], and wind farm layouts [26][27][28]. The objective function is defined in terms of blade mass and its location, moment of inertia, and frequencies (flapwise and edgewise).…”

Section: Introductionmentioning

confidence: 99%

A Simplified Blade Model for Reliable Seismic Assessments of Wind Turbines

Ali¹,

Risi²

2021

14th WCCM-ECCOMAS Congress

View full text Add to dashboard Cite

Wind turbines are dynamically complex structures. They entail slender towers, flexible foundations, and heavy rotor-nacelle-assembly (RNA). In the context of earthquake analysis, the RNA is often simplified as a rigid point mass which can suppress the modal contribution of blades from the global system dynamics and may further affect the reliability of seismic response of wind turbines. Other high-fidelity finite element (FE) blade models are difficult to implement due to the complex layup of composite materials and reduced computational efficiency. Thus, there is a need for an intermediate solution that allows the realistic and accurate consideration of blades in the seismic assessment of wind turbines. This study presents a meta-heuristic, problem-independent optimisation method, known as the genetic algorithm (GA), to identify simplified material and cross-sectional properties of a typical wind turbine blade. The properties are used to construct a simplified FE blade model that can be implemented in global wind turbine models. The optimised design solutions are examined with regards to the mechanical and dynamic response of a reference 5MW wind turbine having 61.5 m long blades. The accuracy of the modal behaviour validates the presented optimisation and simplified blade modelling approach and signifies the potential of its application in seismic assessments of wind turbines.

show abstract

Numerical determination for solving the symmetric eigenvector problem using genetic algorithm

Cited by 9 publications

References 2 publications

Numerical Non-Linear Modelling Algorithm Using Radial Kernels on Local Mesh Support

Numerical Non-Linear Modelling Algorithm Using Radial Kernels on Local Mesh Support

Finite element modeling optimization of wind turbine blades from an earthquake engineering perspective

A Simplified Blade Model for Reliable Seismic Assessments of Wind Turbines

Contact Info

Product

Resources

About